Convolutions in Image Processing - MIT 18.S191 Fall 2020 - Week 1

Convolutions in Image Processing - MIT 18.S191 Fall 2020 - Week 1

The Julia Programming Language via YouTube Direct link

- Box blur as an average

2 of 22

2 of 22

- Box blur as an average

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Classroom Contents

Convolutions in Image Processing - MIT 18.S191 Fall 2020 - Week 1

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  1. 1 - Introduction
  2. 2 - Box blur as an average
  3. 3 - Dealing with the edges
  4. 4 - Gaussian blur
  5. 5 - Visualizing gaussian blur
  6. 6 - Convolution
  7. 7 - Kernels and the gaussian kernel
  8. 8 - Looking at the convolution in Julia
  9. 9 - Julia: `ImageFiltering` package and Kernels
  10. 10 - Julia: `OffsetArray` with different indices
  11. 11 - Visualizing a kernel
  12. 12 - Computational complexity
  13. 13 - Julia: `prod` function for a product
  14. 14 - Example of a non-blurring kernel
  15. 15 - Sharpening edges in an image
  16. 16 - Edge detection with Sobel filters
  17. 17 - Relation to polynomial multiplication
  18. 18 - Convolution in polynomial multiplication
  19. 19 - Relation to Fourier transforms
  20. 20 - Fourier transform of an image
  21. 21 - Convolution via Fourier transform is faster
  22. 22 - Final thoughts

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